Fast object extraction based on wavelet transform and graph cuts

doi:10.3778/j.issn.1002-8331.2010.33.061

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (33): 215-217.DOI: 10.3778/j.issn.1002-8331.2010.33.061

• 图形、图像、模式识别 • Previous Articles Next Articles

Fast object extraction based on wavelet transform and graph cuts

WANG Jian-qing¹，GUO Min¹，XU Qiu-ping^1，2

1.School of Computer Science，Shaanxi Normal University，Xi’an 710062，China
2.Instructional Technology Centre of Engineering College of Armed Police Force，Xi’an 710086，China

Received:2009-03-23 Revised:2009-05-18 Online:2010-11-21 Published:2010-11-21
Contact: WANG Jian-qing

结合小波变换与图像分割的快速目标提取

王建青¹，郭敏¹，徐秋平^1，2

1.陕西师范大学计算机科学学院，西安 710062
2.武警工程学院教育技术中心，西安 710086

通讯作者: 王建青

Abstract

Abstract: GrabCut algorithm based on graph cuts has the global optimality and the unity of combining multiple knowledge.However，such algorithm is less efficient because it uses the whole pixels to initialize the GMM parameters and uses iterative algorithm to obtain exactitude.On the basis of GrabCut algorithm，this paper processes the image using wavelet transform，and then estimates the GMM parameters with low-frequency image’s pixels，sharply decreases the problem scale.The experiments show that this method significantly improves the algorithm’s efficiency.

Key words: wavelet transform, graph cuts, Gaussian Mixture Model（GMM）, object extraction

摘要： 基于图割理论的GrabCut算法具有全局最优性和结合多种知识的统一性，但其基于全部像素点的参数估计以及为达到一定分割精度采取的迭代求解模式，使算法效率大大降低。以GrabCut算法为基础，通过小波变换将图像分解，用分解后低频图像的像素点作为GMM参数迭代估计的样本点，减小了问题规模。实验结果表明，算法的效率得到较大提高。

关键词: 小波变换, 图像分割, 高斯混合模型, 目标提取

CLC Number:

TP391

WANG Jian-qing¹，GUO Min¹，XU Qiu-ping^1，2. Fast object extraction based on wavelet transform and graph cuts[J]. Computer Engineering and Applications, 2010, 46(33): 215-217.

王建青¹，郭敏¹，徐秋平^1，2. 结合小波变换与图像分割的快速目标提取[J]. 计算机工程与应用, 2010, 46(33): 215-217.

[1]	DU Xiuli, MA Zhenqian, QIU Shaoming, LYU Yana. Recognition of Motor Imaging EEG Signals Based on Convolution Attention Mechanism [J]. Computer Engineering and Applications, 2021, 57(18): 181-185.
[2]	FAN Wenbing, SUN Zhiyuan. SAR Image Segmentation Algorithm Based on Generalized Gauss Distribution in Wavelet Domain [J]. Computer Engineering and Applications, 2020, 56(5): 222-226.
[3]	CAO Jun, CHEN He, ZHANG Jiawei. Research on Multi-Focus Image Fusion Algorithm Based on Super Resolution [J]. Computer Engineering and Applications, 2020, 56(3): 180-186.
[4]	GONG Rui, WANG Xiaochun. Multi-Focus Image Fusion Method Based on C-EWT [J]. Computer Engineering and Applications, 2020, 56(2): 201-210.
[5]	GU Tingting, LIU Xinhui, SANG Qingbing, LI Chaofeng. No-Reference Image Quality Assessment Algorithm for Stereoscopic Images via Dual-Tree Complex Wavelet Transform [J]. Computer Engineering and Applications, 2019, 55(2): 154-161.
[6]	YANG Xia, ZHU Xiaodong, LIU Yuanning, FENG Jiakai, LIU Shuai. Iris Recognition Method Based on Block Wavelet Feature Combined with BP Neural Network [J]. Computer Engineering and Applications, 2019, 55(18): 132-139.
[7]	XIAO Wenqing1,3, WANG Honghao2, ZHAN Chang’an1. Wavelet Coefficient Feature Fusion Based Classification of Mice Epileptic EEG [J]. Computer Engineering and Applications, 2019, 55(14): 155-161.
[8]	XIE Guobo, WU Zhenyu. Chaotic Image Encryption Algorithm Based on Wavelet Transform and Gravity Model [J]. Computer Engineering and Applications, 2019, 55(13): 100-105.
[9]	YAN Hongwen, LU Geyu. Application research on complete ensemble empirical mode decomposition, wavelet transform and convolutional neural networks in short-term wind speed forecasting [J]. Computer Engineering and Applications, 2018, 54(9): 224-230.
[10]	ZHANG Zhiyu1, LI Xiangyue1, LI Xiangyang2. Research on random noise suppression by synchrosqueezing wavelet transform [J]. Computer Engineering and Applications, 2018, 54(5): 57-60.
[11]	CHEN Bo1, LIU Houquan1, ZHAO Zhikai2. Method of multi-scale anomaly detection in time series [J]. Computer Engineering and Applications, 2018, 54(20): 122-127.
[12]	JIA Pengtao, JIA Wei. Recherche algorithm on coal mine multi-target trajectory tracking [J]. Computer Engineering and Applications, 2018, 54(2): 222-227.
[13]	ZHANG Yichao, YUAN Zhenming, SUN Xiaoyan. Sleep position recognition based on ballistocardiogram signal [J]. Computer Engineering and Applications, 2018, 54(17): 135-140.
[14]	HUANG Yafei, WANG Guofu, ZHANG Faquan, YE Jincai. Image denoising method based on bee colony algorithm and parametric threshold function [J]. Computer Engineering and Applications, 2018, 54(17): 164-168.
[15]	WANG Lei, SUN Wei, CHEN Yibo, LI Peng, ZAHO Lingxiao. ECG denoising method based on adaptive wavelet threshold selection [J]. Computer Engineering and Applications, 2018, 54(15): 29-33.

Fast object extraction based on wavelet transform and graph cuts

结合小波变换与图像分割的快速目标提取

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics